Machine guidance system for terrain detection and/or autonomous excavation using a construction asset

Abstract

A machine guidance system and method utilize optical sensors, position sensors, and movement sensors to generate point cloud data for a construction asset. Data encompassing terrain features, obstacles, and the real-world position and orientation of the asset and its attachment are calculated. The fused data is used to autonomously control the movement of the asset and the position of the attachment to maintain a cutting edge at a target grade. As a result, terrain mapping and obstacle detection are performed in real-time, enabling safe and efficient operation without predefined paths. In this manner, applications include automated earthmoving, grading, and material handling in dynamic construction environments.

What is claimed is: 
     
         1 . A method comprising:
 receiving point cloud data from one or more than one optical sensor mounted on a construction asset having a machine guidance system, the point cloud data representing portions of terrain and obstacles outside of the asset;   filtering the point cloud data that is received based on one or more than one predetermined thresholds and applying one or more spatial filters to isolate features of the terrain from the point cloud data that is filtered;   processing the point cloud data that is filtered to identify terrain features and obstacles;   autonomously controlling movement of the asset and an attachment to the asset while performing one or both of excavation or material dumping at a worksite using the terrain features and the obstacles that are identified;   receiving position data and movement data from one or more than one position or movement sensor mounted to the asset;   fusing the point cloud data that is filtered, the position data, and the movement data to calculate a real-world position, orientation, and a calculated position of a cutting edge of the attachment; and   autonomously controlling the asset to adjust the position and the orientation of the attachment to maintain the calculated position of the cutting edge of the attachment at a target grade during at least some of the movement of the asset that is autonomously controlled.   
     
     
         2 . The method of  claim 1 , further comprising:
 calculating an estimated elevation of the cutting edge of the attachment relative to a ground surface using the calculated position of the cutting edge and comparing the estimated elevation with a target grade to determine a deviation,   wherein autonomously controlling the asset to adjust the position and the orientation of the attachment to maintain the calculated position of the cutting edge at the target grade is performed using the deviation.   
     
     
         3 . The method of  claim 1 , further comprising:
 receiving an excavation location and a pile location,   wherein the movement of the asset is autonomously controlled between the excavation location and the pile location and the point cloud data that is filtered is processed to identify the terrain features and the obstacles while the asset is moving between the excavation location and the pile location.   
     
     
         4 . The method of  claim 3 , wherein the movement of the asset is autonomously controlled between the excavation location and the pile location without a previously defined path being received, calculated, or obtained. 
     
     
         5 . The method of  claim 1 , wherein filtering the point cloud data includes removing data points associated with a reflectivity value that is below a predetermined threshold and applying one or more than one box filter to isolate the data points associated with the terrain features from the data points associated with the asset. 
     
     
         6 . The method of  claim 1 , further comprising:
 generating a terrain map of an area surrounding the asset using the point cloud data that is filtered, the position data, and the movement data that is fused.   
     
     
         7 . The method of  claim 6 , wherein generating the terrain map comprises dividing the area surrounding the construction asset into a grid of cells, and for each of the cells, calculating an elevation value based on elevations of data points in the point cloud data that are projected into that cell. 
     
     
         8 . The method of  claim 7 , further comprising:
 updating only the cells in the grid of the terrain map that correspond to locations with newly received or modified point cloud data.   
     
     
         9 . A machine guidance system comprising:
 one or more than one optical sensor mounted on an asset, the one or more than one optical sensor sensing an area around the asset and outputting point cloud data representative of portions of terrain and obstacles outside of the asset;   one or more than one position sensor mounted on the asset and configured to output position data indicative of geographic positions of the one or more than one position sensor;   a movement sensor mounted on the asset and configured to output movement data indicative of movement of the movement sensor; and   a processing unit configured to receive and filter the point cloud data that is received based on one or more predetermined thresholds and by applying one or more spatial filters to isolate features of the terrain from the point cloud data that is filtered, the processing unit examining the point cloud data that is filtered to identify terrain features and obstacles and autonomously controlling movement of the asset and an attachment to the asset using the terrain features and the obstacles that are identified, the processing unit configured to fuse the point cloud data that is filtered, the position data, and the movement data to calculate a real-world position, orientation, and a calculated position of a cutting edge of an attachment to the asset, the processing unit configured to autonomously control the asset to adjust the position and the orientation of the attachment to maintain the calculated position of a cutting edge of the attachment at a target grade during at least some of the movement of the asset that is autonomously controlled.   
     
     
         10 . The machine guidance system of  claim 9 , wherein the processing unit is configured to calculate an estimated elevation of the cutting edge of the attachment relative to a ground surface using the calculated position of the cutting edge and comparing the estimated elevation with a target grade to determine a deviation,
 wherein the processing unit is configured to autonomously control the asset to adjust the position and the orientation of the attachment to maintain the calculated position of the cutting edge at the target grade using the deviation.   
     
     
         11 . The machine guidance system of  claim 9 , wherein the processing unit is configured to receive an excavation location and a pile location, and the processing unit is configured to autonomously control the movement of the asset between the excavation location and the pile location and the processing unit is configured to identify the terrain features and the obstacles from the point cloud data that is filtered while the asset is moving between the excavation location and the pile location. 
     
     
         12 . The machine guidance system of  claim 11 , wherein the processing unit autonomously controls the movement of the asset between the excavation location and the pile location without a previously defined path being received, calculated, or obtained. 
     
     
         13 . The machine guidance system of  claim 9 , wherein the processing unit is configured to filter the point cloud data by removing data points associated with a reflectivity value that is below a predetermined threshold and by applying one or more than one box filter to isolate the data points associated with the terrain features from the data points associated with the asset. 
     
     
         14 . The machine guidance system of  claim 9 , wherein the processing unit is configured to generate a terrain map of an area surrounding the asset using the point cloud data that is filtered, the position data, and the movement data that is fused. 
     
     
         15 . The machine guidance system of  claim 14 , wherein the processing unit is configured to generate the terrain map by dividing the area surrounding the construction asset into a grid of cells, and for each of the cells, calculating an elevation value based on elevations of data points in the point cloud data that are projected into that cell. 
     
     
         16 . The machine guidance system of  claim 15 , wherein the processing unit updates only the cells in the grid of the terrain map that correspond to locations with newly received or modified point cloud data. 
     
     
         17 . A method comprising:
 identifying an excavation location where a construction asset is to excavate material using an attachment to the asset;   identifying a pile location where the construction asset is to pile the material that is excavated;   obtaining point cloud data from light detection and ranging (LiDAR) sensors onboard the asset;   processing the point cloud data to identify terrain features and obstacles outside of the asset, and to calculate a position of a cutting edge of the attachment; and   autonomously controlling the asset to excavate the material at the excavation location using the position of the cutting edge of the attachment that is calculated, to move the asset to the pile location without colliding with the obstacles and without a previously defined or calculated path between the excavation location and the pile location being obtained, and to dump the material at the pile location using the point cloud data.   
     
     
         18 . The method of  claim 17 , wherein the point cloud data is obtained by the LiDAR sensors measuring reflection off reflective surfaces on the asset and the attachment. 
     
     
         19 . The method of  claim 17 , wherein the point cloud data is processed to identify the terrain features and the obstacles by applying one or more than one box filter associated with the asset and with the attachment to the point cloud data. 
     
     
         20 . The method of  claim 17 , further comprising:
 receiving position data from one or more than one global navigation satellite system (GNSS) receivers onboard the asset;   receiving movement data from an inertial measurement unit (IMU) onboard the asset; and   generating a terrain map of an area surrounding the asset by fusing the point cloud data, the position data, and the movement data.